{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d6c0bfea-ca4d-4e02-8e6c-d710bdfea9f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T14:50:51.876990Z",
     "iopub.status.busy": "2024-11-29T14:50:51.876990Z",
     "iopub.status.idle": "2024-11-29T14:50:52.169516Z",
     "shell.execute_reply": "2024-11-29T14:50:52.168402Z",
     "shell.execute_reply.started": "2024-11-29T14:50:51.876990Z"
    }
   },
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "# 设置中文字体，这里以微软雅黑为例\n",
    "matplotlib.rcParams['font.family'] = 'Microsoft YaHei'\n",
    "matplotlib.rcParams['font.size'] = 12  # 可以设置字体大小"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b07443d6-146f-4516-aec3-54f1e64ded23",
   "metadata": {},
   "source": [
    "# 折线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d9f893ef-0103-4938-81f2-b197a62c6296",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T13:44:42.109477Z",
     "iopub.status.busy": "2024-11-29T13:44:42.109477Z",
     "iopub.status.idle": "2024-11-29T13:44:42.251619Z",
     "shell.execute_reply": "2024-11-29T13:44:42.251619Z",
     "shell.execute_reply.started": "2024-11-29T13:44:42.109477Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2a62a7f43d0>]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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c8Fj9ddCzC4JwPuCclqlfcceALkmS1Fib18G7T8I7f4NVc3acT8mEfl8IRssPORlS0vb8OAPOgX5nNryTqNosA7okSdK+qNwMi58PQvnSGRCrDs5HkuDgzwWhvP9ZkN6hcY+blAx9T2ryctV6GdAlSZJ2p3obLPtvMH3lvWehavOO+wqODkL5oPOgQ35oJSrxGNAlSZJ2FovB6nmwYAos/Ads/mTHfZ367Gj2POiw0EpUYjOgS5IkAXz6YbACyztTYP2HO8636wwDzwtCeY/h9Zs9pSZmQJckSW3Xpk+CnT3fmQKr39xxPiUzaN4cciEc8nlITg2vRrU5BnRJkpQYotX7thpK5WZ4/19BKP/wP3WbPQ85OZjC0u9MSM9q2fqlGgZ0SZLU+i2aupv1xO8MljKs3gYfvRSE8vefhaotO67rPnRHs2dW15avXdqFAV2SJLVui6bW7MgZq3u+bA1M+Socemqww+eWdTvuyz14R7Nn50NatFxpbwzokiSp9YpWByPnu4Zz2HFu6fTg33YHwaCxwbzy7sfY7Km4ZUCXJEmt1/LX6k5r2Z1RP4YRV9rsqVYhKewCJEmS9tum4n27Lqen4VythgFdkiS1TrEYrPtg367NymveWqQm5BQXSZLU+qx9H56/Dpa9vJcLI8FqLr1HtkhZUlNwBF2SJLUe5WXwwg/hwROCcJ6SEezySaTmtrOa49PvaHg9dClOOYIuSZLiXywG7/wNpt+8Y955v7Ng9M+gU28Y+MXdrIN+R7AOutSKGNAlSVJ8W/MOPHcdrHw9OM49BM64Cw4bteOaAecEu3/uy06iUpwzoEuSpPi0dQP853Z48xGIRSG1PXz2Ojj+O5CSXv/6pGToe1LL1yk1MQO6JEmKL9EovPUnmHErbPk0ODfwPDjtNsjpHm5tUgswoEuSpPixai48dy0UzguOu/SHL9wFfT8Tbl1SCzKgS5Kk8G1eF4yYz/sTEIP0bPjcRDj2624wpDbHgC5JksJTvQ3mPgr/+SmUlwbnjvwyjPoxdHBzIbVNBnRJkhSO5bOC1VmKFwTH+YPhC7+AXseHW5cUMgO6JElqWRuLgvXM3/lbcJzREU65CYZe5rKIEgZ0SZLUUqqr4I3fwX/vgMqNQASGjoOTb4b2ncOuToobBnRJktT8PvovPHc9rFscHHcfBl/4OXQ/JtSypHhkQJckSc2ndBW88ENY9FRw3K4zjLoVjroEkpJCLU2KVwZ0SZLU9LZVwGv3wiu/hKotEEmC4V+Hz0+EzE5hVyfFNQO6JElqWkumw/PXw/qPguNeI4PNhvIHh1uX1Eo0+r2l1atX85WvfIXOnTuTmZnJ4MGDefPNN2vvj8Vi3HzzzXTr1o3MzExGjRrFkiVLmrRoSZIUh9Yvg79eDH85PwjnWXlw3sNw2XOGc6kRGhXQN2zYwAknnEBqairPP/88ixYt4pe//CWdOu14q+quu+7innvu4cEHH+SNN96gffv2jB49mvLy8iYvXpIkxYGqrfDSz+C+42Dxc5CUAiOvgivfhCEXQCQSdoVSqxKJxWKxfb34xhtv5H//+x+vvPJKg/fHYjEKCgr4/ve/z7XXXgtAaWkpeXl5/OEPf+Ciiy7a69coKysjJyeH0tJSsrOz97U0SZLU0mIxeP9f8MJEKFkRnOv72WB1li5HhFubFIf2Nec2agR96tSpDBs2jC996Ut07dqVo48+mocffrj2/mXLllFUVMSoUaNqz+Xk5HDccccxa9asBh+zoqKCsrKyOjdJkhTn1i2BP4+Fv10ShPPsHvClP8KlTxvOpQPUqID+0Ucf8cADD3DYYYfxwgsv8O1vf5vvfve7/PGPfwSgqKgIgLy8vDqfl5eXV3vfriZNmkROTk7trWfPnvvz/5AkSU0pWg3LXoEFfw/+jVYH5ys2wfRb4P4R8OEMSE6Dk66FK2fDwDFOZ5GaQKNWcYlGowwbNoyf/exnABx99NEsXLiQBx98kHHjxu1XARMnTmTChAm1x2VlZYZ0SZLCtGgqTLsBygp3nMsugIFfhIVPwsaa84edBqffAZ0PCadOKUE1KqB369aNAQMG1DnXv39//vGPfwCQn58PQHFxMd26dau9pri4mKOOOqrBx0xPTyc9Pb0xZUiSpOayaCpMuRTYpUWtrBBm3Rd83LE3nHEnHH66I+ZSM2jUFJcTTjiBxYsX1zn3wQcf0Lt3bwD69u1Lfn4+M2bMqL2/rKyMN954gxEjRjRBuZIkqdlEq4OR813D+c7Ss+Hbs+CIMwznUjNpVEC/5ppreP311/nZz37G0qVLmTx5Mg899BDjx48HIBKJcPXVV3PbbbcxdepUFixYwKWXXkpBQQFjxoxpjvolSVJTWf5a3WktDakog8J5LVOP1EY1aorL8OHDefLJJ5k4cSI/+clP6Nu3L3fffTeXXHJJ7TXXX389mzdv5hvf+AYlJSWceOKJTJs2jYyMjCYvXpIkNaFNxU17naT90qh10FuC66BLkhSS+ZPhqW/v/bpxz0Lfk5q/HinBNMs66JIkKQHFYjDn9/DM1Xu5MALZ3aH3yJaoSmqzGjXFRZIkJZjN6+DpK+GD54PjvEFQ/G7NnTu/yV7TEHr6HZCU3JIVSm2OI+iSJLVVS2fAAyODcJ6cBqMnwTdfgQseg+xuda/NLgjODzgnnFqlNsQRdEmS2pqqcphxK7x+f3DcpR+M/T3kDw6OB5wD/c4MVnXZVAxZecG0FkfOpRZhQJckqS1Z+z784wooXhgcD/86nPZTSM2se11Sso2gUkgM6JIktQXbG0H//SPYVg7tDoJz74MjTg+7Mkm7MKBLkpToNn0CU6+ED6YFx4eOgnPvhw554dYlqUEGdEmSEtmSF4O1zTevDRpBT/0JHPtNSHKdCCleGdAlSUpEVeXw4o/hjQeC4y79axpBB4ValqS9M6BLkpRoihfBP/4frK1Zz/zYbwQj57s2gkqKSwZ0SZISRSwGsx8OGkGrK6B9l2Cu+eGnhV2ZpEYwoEuSlAg2rYWnx8OSfwfHh54KY+6HrK7h1iWp0QzokiS1dh/8G57+Dmz+BJLTg3XNj/0GRCJhVyZpPxjQJUlqrarKYfrNMPt3wXHXATD2EcgbEG5dkg6IAV2SpNao+N2aRtBFwfFx34JRt0JqRrh1STpgBnRJklqTWAze+F0wcr69EXTMA3DYqWFXJqmJGNAlSWotNq0NNh1a+mJwfNhpwSotWV3CrUtSkzKgS5LUGnzwAjz1HdiyDlIy4LTbYPj/sxFUSkAGdEmS4lnVVvj3TTDn4eC460A4/xHo2j/cuiQ1GwO6JEnxqmhh0Aj6yXvB8fHfgVNusRFUSnAGdEmS4k00GiydOP2WmkbQrjWNoKPCrkxSCzCgS5IUTzYWB42gH84Ijg8/Hc69D9ofFG5dklqMAV2SpHixeFqwI+iWT4NG0NG3w7ArbASV2hgDuiRJYavcAtNvgjm/D47zBsPY30PXfuHWJSkUBnRJksJUtAD+fgWsWxwcHz8eRt0CKenh1iUpNAZ0SZKaW7Qalr8Gm4ohKw96jwQi8MYD8OKPoboyOD/mATj0lLCrlRQyA7okSc1p0VSYdgOUFe44l5UfNH0WLwyOj/gCnHOvjaCSAAO6JEnNZ9FUmHIpEKt7flNRcEtKgzPugGGX2wgqqVZS2AVIkpSQotXByPmu4Xxn7TrB0K8ZziXVYUCXJKk5LH+t7rSWhmwqDq6TpJ0Y0CVJag6bipv2OklthgFdkqTmkJXXtNdJajMM6JIkNYf8IZCUuocLIpDdvWbJRUnawYAuSVJT21YBU74K0ardXFDTFHr6HZCU3GJlSWodDOiSJDWl6m3w98th2UxIy4JTfgzZBXWvyS6ACx6DAeeEUqKk+OY66JIkNZVoFKZeBe8/C8npcNFkOPizcMJ36+8k6si5pN0woEuS1BRiMXjhB/D2ZIgkw5ceDcI5BGG870nh1iep1XCKiyRJTWHmnfDGA8HH594H/c4Mtx5JrZYBXZKkA/X6A/DfScHHZ9wFR10cbj2SWjUDuiRJB+Ktv8C0G4OPP/9DOO6b4dYjqdUzoEuStL/eewamXhl8fPx4+Mx14dYjKSEY0CVJ2h8fvhQspxiLwlFfgdG3QyQSdlWSEoABXZKkxlo5Bx6/BKorof85cPZvDOeSmkyjAvqPf/xjIpFInVu/fv1q7y8vL2f8+PF07tyZrKwsxo4dS3FxcZMXLUlSaIrfhb+MharNcMjJMPb3kOyqxZKaTqNH0AcOHMiaNWtqb6+++mrtfddccw3PPPMMTzzxBDNnzqSwsJDzzjuvSQuWJCk0n34If/oilJdCj2Phwj9DSnrYVUlKMI3+kz8lJYX8/Px650tLS3nkkUeYPHkyJ598MgCPPvoo/fv35/XXX+f4449v8PEqKiqoqKioPS4rK2tsSZIkNb+yQvjTmGA30LxBcMkUSGsfdlWSElCjR9CXLFlCQUEBBx98MJdccgkrVqwAYO7cuVRVVTFq1Kjaa/v160evXr2YNWvWbh9v0qRJ5OTk1N569uy5H/8NSZKa0eZP4bExULICcg+Gr/wTMjuFXZWkBNWogH7cccfxhz/8gWnTpvHAAw+wbNkyTjrpJDZu3EhRURFpaWl07Nixzufk5eVRVFS028ecOHEipaWltbeVK1fu139EkqRmUV4WzDlftxg6FMClT0OHvLCrkpTAGjXF5Ywzzqj9eMiQIRx33HH07t2bKVOmkJmZuV8FpKenk57u/D1JUhyq2gqPfxkK34J2neHSp6Bjr7CrkpTgDmiZxY4dO3L44YezdOlS8vPzqayspKSkpM41xcXFDc5ZlyQprlVXwROXwcevQFoH+Mo/oMsRYVclqQ04oIC+adMmPvzwQ7p168bQoUNJTU1lxowZtfcvXryYFStWMGLEiAMuVJKkFhONwlPfhg+eh5QM+PLfoODosKuS1EY0aorLtddey9lnn03v3r0pLCzklltuITk5mYsvvpicnByuuOIKJkyYQG5uLtnZ2Vx11VWMGDFityu4SJIUd2IxeP46WPAEJKXABY9BnxPCrkpSG9KogL5q1SouvvhiPv30U7p06cKJJ57I66+/TpcuXQD49a9/TVJSEmPHjqWiooLRo0dz//33N0vhkiQ1i//cBnN+D0Tgi7+Dw0eHXZGkNiYSi8ViYRexs7KyMnJycigtLSU7OzvsciRJbcn/7oHpNwUfn/krGH5FuPVISij7mnMPaA66JEkJY+4fd4TzU24xnEsKjQFdkqR3n4Rnvhd8fML34KQJ4dYjqU0zoEuS2rYlL8I/vg7EYOjXYNStYVckqY0zoEuS2q7ls+BvX4FoFQw8L5h3HomEXZWkNs6ALklqm9a8A5MvhG1b4dBTgxVbkpLDrkqSDOiSpDZo3VL40xehohR6jQzWOk9JC7sqSQIM6JKktqZkJTx2LmxZB/lD4MuPQ1q7sKuSpFoGdElS27HpE/jTGChbBZ0Pg6/8EzJywq5KkuowoEuS2obyUvjzefDpUsjpCZc+BVldwq5KkuoxoEuSEl/llqAhtOgdaN8FvvoU5PQIuypJapABXZKU2LZVwpRLYcUsSM8JprUcdGjYVUnSbhnQJUmJK1oNT34Dlk6HlEy4ZAp0GxJ2VZK0RwZ0SVJiisXg2Wvg3SchKRUu+jP0Oj7sqiRprwzokqTE9OItMO+PEEmCsQ/DoaPCrkiS9okBXZKUeF75FfzvN8HHZ90NA78YajmS1BgGdElSYpnze5hxa/DxabfB0HHh1iNJjWRAlyQljgV/h39dG3x80rUw8qpw65Gk/WBAlyQlhsXT4MlvAjEY/nU4+UdhVyRJ+8WALklq/T5+FZ4YB9FtMPgCOOMuiETCrkqS9osBXZLUuq2eB5Mvgm3lcPgZMOZ+SPLlTVLrlRJ2AZIk7bNoNSx/DTYVQ1YetOsMfx4LlRuhz0nwpT9AcmrYVUrSATGgS5Jah0VTYdoNUFa441wkCWJRKDgaLv4rpGaEV58kNREDuiQp/i2aClMuBWJ1z8eiwb/Dvw7pHVq8LElqDk7SkyTFt2h1MHK+azivFYGXbg+uk6QEYECXJMW35a/VndZSTwzKVgfXSVICMKBLkuLbpuKmvU6S4pwBXZIU37LymvY6SYpzNolKkuJXtBoWP7eXiyKQXQC9R7ZISZLU3AzokqT4VF4Kf78Clk7f6WSEus2iNbuFnn4HJCW3YHGS1HwM6JKk+LP+o2B30HWLISUTvvgARJLrr4OeXRCE8wHnhFerJDUxA7okKb58/Cr87auwdT106BZsQFRwdHBfvzPr7iTae6Qj55ISjgFdkhQ/5v4R/jUBotug4Bi4aDJkd9txf1Iy9D0pvPokqQUY0CVJ4aveBtNvgtfvD44Hngdj7ofUzHDrkqQQGNAlSeEqL4W/Xw5LXwyOP/9D+Mx1EImEW5ckhcSALkkKT71m0Adh4Jiwq5KkUBnQJUnhWPYKTPkqbN0AHQpqmkGPCrsqSQqdAV2S1PLefBSeu3ZHM+jFf4UO+WFXJUlxwYAuSWo51dvg3z+ENx4MjgeNhXPvsxlUknZiQJcktYytJUEz6IczguPP/wg+c63NoJK0CwO6JKn5ffohTL4QPl0Cqe2CZtAB54ZdlSTFJQO6JKl5fTQTplwK5SWQ3T2Yb97tyLCrkqS4ZUCXJDWfOY/A89cHzaDdh8FFf7EZVJL2woAuSWp61dvghYkw+6HgePCX4JzfQmpGuHVJUiuQdCCffMcddxCJRLj66qtrz5WXlzN+/Hg6d+5MVlYWY8eOpbi4+EDrlCS1Fls3wF/O3xHOT74JznvYcC5J+2i/A/qcOXP43e9+x5AhQ+qcv+aaa3jmmWd44oknmDlzJoWFhZx33nkHXKgkqRX49EP4/Sj46KWgGfTCP7tSiyQ10n4F9E2bNnHJJZfw8MMP06lTp9rzpaWlPPLII/zqV7/i5JNPZujQoTz66KO89tprvP766w0+VkVFBWVlZXVukqRW6KP/wsMnw6dLIbsHXP4C9D877KokqdXZr4A+fvx4zjzzTEaNGlXn/Ny5c6mqqqpzvl+/fvTq1YtZs2Y1+FiTJk0iJyen9tazZ8/9KUmSFKbZD8OfzgtWaukxHL7+H+g2ZK+fJkmqr9FNoo8//jjz5s1jzpw59e4rKioiLS2Njh071jmfl5dHUVFRg483ceJEJkyYUHtcVlZmSJek1qJ6G0y7EeY8HBwPuRDOvsf55pJ0ABoV0FeuXMn3vvc9pk+fTkZG0/zyTU9PJz09vUkeS5LUgrZugCe+FkxtIQKn3AwnXuN8c0k6QI2a4jJ37lzWrl3LMcccQ0pKCikpKcycOZN77rmHlJQU8vLyqKyspKSkpM7nFRcXk5/vureSlDDWLa1pBv0vpLYPmkFPmmA4l6Qm0KgR9FNOOYUFCxbUOXfZZZfRr18/brjhBnr27ElqaiozZsxg7NixACxevJgVK1YwYsSIpqtakhSeD1+CJ8ZBeWnQDPrlxyF/cNhVSVLCaFRA79ChA4MGDapzrn379nTu3Ln2/BVXXMGECRPIzc0lOzubq666ihEjRnD88cc3XdWSpHDMfhievwFi1dDj2GBn0KyuYVclSQmlyXcS/fWvf01SUhJjx46loqKC0aNHc//99zf1l5EktaTqqiCYv/lIcDzkIjj7NzaDSlIziMRisVjYReysrKyMnJwcSktLyc7ODrscSdKW9UEz6LKZQARG3QInXO18c0lqpH3NuU0+gi5JSiCffAB/vRDWfxQ0g479PfT7QthVSVJCM6BLkhq2dAY8cRlUlEJOT7j4ccgftPfPkyQdEAO6JKmuWAxmPwTTJgbNoD2PD5ZRzOoSdmWS1CYY0CWprYpWw/LXYFMxZOVB75EQi8Jz18HcR4NrjvwynH03pLihnCS1FAO6JLVFi6bCtBugrHDHuQ75kNEJPnkPiMCpt8LI79oMKkktzIAuSW3Noqkw5VJgl0W8NhYFt5QM+NIf4IgzwqhOktq8pLALkCS1oGh1MHK+azjfWUY2HHZai5UkSarLgC5Jbcny1+pOa2nIprXBdZKkUBjQJakt2VTctNdJkpqcAV2S2pKsvKa9TpLU5GwSlaS2omorLHpqLxdFILsgWHJRkhQKA7oktQVFC+Ef/69mCcXtItRtFq1ZTvH0OyApuQWLkyTtzCkukpTIYjF4/QF4+OQgnLfvCpf8Ay74E2R3q3ttdgFc8BgMOCecWiVJgCPokpS4NhbD09+BpS8Gx4efDuf8FrK6BMf9zqy/k6gj55IUOgO6JCWixdPg6fGwZV2w8dBpt8Hw/1d3V9CkZOh7Ung1SpIaZECXpERStRX+fRPMeTg4zhsEY38PXfuHW5ckaZ8Z0CUpURQtqGkEfT84Pn48nHIzpGaEW5ckqVEM6JLU2kWj8MYD8OKPoboymE8+5n44dFTYlUmS9oMBXZJas41F8NS34cP/BMeHnwHn/hbaHxRuXZKk/WZAl6TW6v3nYOqVsOXToBF09O0w7Iq6jaCSpFbHgC5JrU3lFvj3j+DNR4LjvMFw/iPQ5Yhw65IkNQkDuiS1JmveCRpB1y0OjkdcGTSCpqSHW5ckqckY0CWpNYhG4fX7YcatNY2g+fDFB+CQk8OuTJLUxAzokhTvytYEjaAfvRQcH3EmnHMvtO8cbl2SpGZhQJekePb+v+DpK2HrekjJhNMnwdCv2QgqSQnMgC5J8ahyC7zwA5j7aHCcPwTGPgJdDg+3LklSszOgS1K8WfM2/P0K+HRJcDzyKjj5JhtBJamNMKBLUryIRmHWb2HGTyBaBR26wZgH4JDPh12ZJKkFGdAlKR6UFcKT34JlM4PjfmcFjaDtcsOtS5LU4gzokhS2954NdgTdugFS2wWNoMeMsxFUktooA7okhaVyc00j6B+C425HBo2gBx0WalmSpHAZ0CUpDIXzgx1BP10CROCE78LnfwQpaWFXJkkKmQFdklpSNAqv3QP/ua2mEbQAvvggHPzZsCuTJMUJA7oktZTS1fDUt2DZy8Fx/7Ph7HtsBJUk1WFAl6SWsGgqTL0KykuCRtAz7oSjv2ojqCSpHgO6JDWnys0w7UaY91hwXHA0nPd7OOjQcOuSJMUtA7okNYVoNSx/DTYVQ1Ye9B4Z7Aj6z6/Dp0uBCJx4NXzuBzaCSpL2yIAuSQdq0VSYdkOw2dB26dlQuQli0aAR9LyHoO9J4dUoSWo1DOiSdCAWTYUplwKxuucryoJ/ewyHL0+xEVSStM+Swi5AklqtaHUwcr5rON9ZWSFk5LRYSZKk1s+ALkn7a/lrdae1NKRsdXCdJEn7yIAuSfujugrefXLfrt1U3Ly1SJISSqMC+gMPPMCQIUPIzs4mOzubESNG8Pzzz9feX15ezvjx4+ncuTNZWVmMHTuW4mJfmCQlkKqtMPthuOcYePORffucrLzmrUmSlFAaFdB79OjBHXfcwdy5c3nzzTc5+eSTOffcc3n33XcBuOaaa3jmmWd44oknmDlzJoWFhZx33nnNUrgktajyUnjlV3D3YHjuWihdAe26BKu1sLvNhiKQ3T1YclGSpH0UicVie+hu2rvc3Fx+/vOfc/7559OlSxcmT57M+eefD8D7779P//79mTVrFscff/w+PV5ZWRk5OTmUlpaSnZ19IKVJ0oHbvA5efyAYNa8oDc7l9IITvgtHfwWWTK9ZxQXqNovWhPYLHoMB57RkxZKkOLWvOXe/l1msrq7miSeeYPPmzYwYMYK5c+dSVVXFqFGjaq/p168fvXr12mNAr6iooKKiok7hkhS60lXw2r0w94+wbWtw7qAj4KQJMGgsJKcG5wacE4TwXddBzy6A0+8wnEuSGq3RAX3BggWMGDGC8vJysrKyePLJJxkwYADz588nLS2Njh071rk+Ly+PoqKi3T7epEmTuPXWWxtduCQ1i3VL4X+/hrf/BtGq4FzB0XDS9+GIMyGpgZmBA86BfmfW30k0Kblla5ckJYRGB/QjjjiC+fPnU1payt///nfGjRvHzJkz97uAiRMnMmHChNrjsrIyevbsud+PJ0n7Zc3bwRzzRU9TO1Wlz0nBiPnBn4fI7uaZ10hKdqdQSVKTaHRAT0tL49BDDwVg6NChzJkzh9/85jdceOGFVFZWUlJSUmcUvbi4mPz8/N0+Xnp6Ounp6Y2vXJKawvLXgmC+dPqOc4efEQTznseGV5ckqc3a7zno20WjUSoqKhg6dCipqanMmDGDsWPHArB48WJWrFjBiBEjDrhQSWoysRgsfRFe+SWsmBWciyQFc8tPvAbyBoZbnySpTWtUQJ84cSJnnHEGvXr1YuPGjUyePJn//ve/vPDCC+Tk5HDFFVcwYcIEcnNzyc7O5qqrrmLEiBH7vIKLJDWraHUwheXVX0HRguBcchoc9WU44XuQe3C49UmSRCMD+tq1a7n00ktZs2YNOTk5DBkyhBdeeIFTTz0VgF//+tckJSUxduxYKioqGD16NPfff3+zFC5J+2xbJbzzN3j117D+w+BcansYdhmMuBKyu4VbnyRJOzngddCbmuugS2oylZth3mPBcollq4NzGR3huG/Bcd+EdrmhlidJaluafR10SYpbW0tgzsPBBkNbPg3OZeXDyCth6NcgvUOY1UmStEcGdEmJY9NamHUfzHkEKjcG5zr1gROuhiMvhtSMMKuTJGmfGNAltX4blgfTWN76E2wrD851HQAnToCBX4Rkf9VJkloPX7UktV6fLA4aP9+ZArHq4Fz3YcGun4ef3vCun5IkxTkDuqT4E60ONhDaVAxZedB7ZLBT53ar5wabC73/L2p3/Tz4c0Ew73PS3nf9lCQpjhnQJcWXRVNh2g1QVrjjXHYBnH4HZOYGmwt99NKO+/qdFez62X1oy9cqSVIzMKBLih+LpsKUS6kdFd+urLDmfI1IMgz+Epx4NXTt35IVSpLU7AzokuJDtDoYOd81nO9q2OXBrp+d+rREVZIktTg7qCTFh+Wv1Z3WsjsDzzOcS5ISmgFdUnzYVNy010mS1EoZ0CWFr7wM3ntm367NymveWiRJCplz0CWFJxaDd/4G/74JNq/dy8WRYDWX3iNbpDRJksLiCLqkcKx5B/7vdHjym0E4zz0ETroOiNTcdlZzfPoddddDlyQpATmCLqllbVkPL/0M3nwEYlFIbQefuQ5GjIeUdOg2ZPfroA84J7y6JUlqIQZ0SS0jGoW3/gQzboUtnwbnBp4Hp/0UcnrsuG7AOdDvzD3vJCpJUgIzoEtqfqvmwnPXQuG84LhLP/jCz6HvZxq+PikZ+p7UcvVJkhRHDOiSms/mdcGI+bw/ATFIz4bPTYRjvw7JqWFXJ0lSXDKgS2p61dtg7qPwn59CeWlw7siLYdSt0MFlEiVJ2hMDuqSmtXwWPHcdFC8IjvMHwxd+Ab2OD7cuSZJaCQO6pKaxsQim3xysaw6Q0RFOuQmGXmaDpyRJjWBAl3Rgqqvgjd/Bf++Ayo1ABI65FE65Bdp3Drs6SZJaHQO6pP330X/hueth3eLguPvQYHWW7kNDLUuSpNbMgC6p8UpXwQs/hEVPBcftOgcNoEddAkluUCxJ0oEwoEvad9sqYNZv4eVfQNUWiCTB8P8Hn/8BZHYKuzpJkhKCAV3SvlkyHZ6/HtZ/FBz3GhFMZ8kfHG5dkiQlGAO6pD1bvwxe+AEsfi44zsqD026DwV+CSCTc2iRJSkAGdEkNq9oKr94Nr/4aqisgKQWO/zZ85nrIyA67OkmSEpYBXVJdsRi8/y94YSKUrAjO9f1sMJ2lyxHh1iZJUhtgQJe0w7qlwTzzD2cEx9k9YPTtMOBcp7NIktRCDOiSoGITvPILeO23EK2C5DQY+V04aQKktQ+7OkmS2hQDutSWxWLw7j/hhR/BxsLg3GGnwel3QOdDwq1NkqQ2yoAuJbJoNSx/DTYVB6uv9B4JScnBfcWLguksH78SHHfsDWfcCYef7nQWSZJCZECXEtWiqTDtBigr3HEuuwBOuQXWvANvPAixakjJgJO+H0xpSc0Ir15JkgQY0KXEtGgqTLkUiNU9X1YIT35zx3G/s2D0z6BT7xYtT5Ik7Z4BXUo00epg5HzXcL6zpBS4aDIcPrrFypIkSfsmKewCJDWx5a/VndbSkOg2SG3XMvVIkqRGMaBLiWZTcdNeJ0mSWpQBXUo0WV338bq85q1DkiTtF+egS4lk01p49Td7uSgSrObSe2SLlCRJkhrHgC4lig9egKe+A1vWQVJqsCMoEeo2i9asb376HTvWQ5ckSXHFKS5Sa1e1FZ67DiZfEITzrgPhW6/ABX+C7G51r80ugAsegwHnhFOrJEnaK0fQpdasaCH84//BJ+8Fx8d/J9iIKDUDuvaHfmfufidRSZIUlwzoUmsUjcLs38H0W6C6Atp3hTEPwGGj6l6XlAx9TwqnRkmStF8aNcVl0qRJDB8+nA4dOtC1a1fGjBnD4sWL61xTXl7O+PHj6dy5M1lZWYwdO5biYpdzk5rMxmL4y/kw7cYgnB9+OnxnVv1wLkmSWqVGBfSZM2cyfvx4Xn/9daZPn05VVRWnnXYamzdvrr3mmmuu4ZlnnuGJJ55g5syZFBYWct555zV54VKbtHgaPDACPpwBKRlw5i/h4seh/UFhVyZJkppIJBaL7WE/8D375JNP6Nq1KzNnzuQzn/kMpaWldOnShcmTJ3P++ecD8P7779O/f39mzZrF8ccfv9fHLCsrIycnh9LSUrKzs/e3NCmxVG6B6TfBnN8Hx3mDYezvoWu/cOuSJEn7bF9z7gHNQS8tLQUgNzcXgLlz51JVVcWoUTveau/Xrx+9evXabUCvqKigoqKiTuGSdlK0AP5+BayrmU52/HgYdQukpIdblyRJahb7vcxiNBrl6quv5oQTTmDQoEEAFBUVkZaWRseOHetcm5eXR1FRUYOPM2nSJHJycmpvPXv23N+SpMQSjcKs++Dhk4NwnpUHX/knnP4zw7kkSQlsvwP6+PHjWbhwIY8//vgBFTBx4kRKS0trbytXrjygx5MSwsYi+MtYeOEHUF0JR3wBvv0aHHpK2JVJkqRmtl9TXK688kqeffZZXn75ZXr06FF7Pj8/n8rKSkpKSuqMohcXF5Ofn9/gY6Wnp5Oe7migVOv952DqlbDlU0jJhNG3w7DLIRIJuzJJktQCGjWCHovFuPLKK3nyySf5z3/+Q9++fevcP3ToUFJTU5kxY0btucWLF7NixQpGjBjRNBVLiapyCzx7DTx+cRDO8wfDN2fC8CsM55IktSGNGkEfP348kydP5umnn6ZDhw6188pzcnLIzMwkJyeHK664ggkTJpCbm0t2djZXXXUVI0aM2KcVXKQ2a807wY6g2xtBR1wJp9zsXHNJktqgRi2zGNnNKN6jjz7K1772NSDYqOj73/8+f/3rX6moqGD06NHcf//9u53isiuXWVSbEo3C6/fBi7dCtAqy8uGLD8AhJ4ddmSRJamL7mnMPaB305mBAV5tRtgae+hZ89N/g+Igz4Zx7oX3nUMuSJEnNo0XWQZe0n957FqZeBVvXB42gp0+CoV9zrrkkSTKgSy2qcnOwdOLcPwTH+UNg7CPQ5fBQy5IkSfHDgC61lDVvBzuCfrokOB75XTj5RzaCSpKkOgzoUnOLRmHWb2HGT4JG0A7d4IsPwsGfC7sySZIUhwzoUnMqK4QnvwXLZgbH/c4KGkHb5YZblyRJilsGdKm5vPdMTSPoBkhtFzSCHjPORlBJkrRHBnSpqVVuhmkTYd4fg+NuRwaNoAcdFm5dkiSpVTCgS02p8K1gR9BPlwIROOG78PkfQUpa2JVJkqRWwoAuNYVoFF67B/5zW00jaEFNI+hnw65MkiS1MgZ06UCVroYnvwkfvxIc9z8bzr7HRlBJkrRfDOjSvopWw/LXYFMxZOVB75Hw/rMw9btQXhI0gp5xJxz9VRtBJUnSfjOgS/ti0VSYdkOwbOJ2qe2gakvwcbejahpBDw2lPEmSlDgM6NLeLJoKUy4FYnXPbw/n/c6C8x+1EVSSJDWJpLALkOJatDoYOd81nO+s8C1ISm6xkiRJUmIzoEt7svy1utNaGlK2OrhOkiSpCRjQpT3ZVNy010mSJO2FAV3ak/KyfbsuK69565AkSW2GTaLS7iz8J0y7cS8XRSC7IFhyUZIkqQk4gi7tKhqFlybB3y+D6grodiQQqbntrOb49DtsEpUkSU3GgC7trHJLEMxn3hEcj7gSvv4SXPAYZHere212QXB+wDktX6ckSUpYTnGRtisrhL9eDGvmQ1IqnPUrOObS4L4B50C/M+vvJOrIuSRJamIGdAlg9Vz465dhUxG06wwX/An6nFD3mqRk6HtSOPVJkqQ2w4AuLfg7PD0etpVDl/7w5cehU5+wq5IkSW2UAV1tVzQK/50EL98VHB82Gsb+HjKyw61LkiS1aQZ0tU2Vm+HJb8F7U4PjkVfBqFudUy5JkkJnQFfbU7oa/noRFL0TNIOe/Rs4+pKwq5IkSQIM6GprVr0Jj385WImlXWe48C/Qe0TYVUmSJNUyoKvteOeJoBm0ugK6DoCLH4dOvcOuSpIkqQ4DuhJfNAov3Q6v/CI4PvwMGPswpHcIty5JkqQGGNCV2Co3w5PfhPeeCY5P+B6ccovNoJIkKW4Z0JW4SlfVNIMugOS0oBn0qC+HXZUkSdIeGdCVmFbOCZpBN6+FdgfBRZOh13FhVyVJkrRXBnQlnnemwNNXBs2geYPg4r9Cx15hVyVJkrRPDOhKHNEo/Oen8OqvguMjzoTzHoL0rHDrkiRJagQDuhJDxaagGfT9Z4PjE6+Bk2+GpKRw65IkSWokA7pav5KV8NeLobimGfSce+HIi8KuSpIkab8Y0NW6rZxd0wz6CbTvEjSD9jw27KokSZL2mwFdrdfbj8PUq6C6EvIG1zSD9gy7KkmSpANiQFfrE43CjFvhf3cHx/3Ogi/+zmZQSZKUEAzoal0qNsE/vwGL/xUcn/R9+PyPbAaVJEkJw4Cu1qNkRU0z6EJITodzfwtDLgi7KkmSpCZlQFfrsOJ1ePwS2LIO2netaQYdHnZVkiRJTc6Arvg3fzI8872gGTR/MFz8OOT0CLsqSZKkZtHoibsvv/wyZ599NgUFBUQiEZ566qk698diMW6++Wa6detGZmYmo0aNYsmSJU1Vr9qSaDVMvxme+nYQzvufDZe/YDiXJEkJrdEBffPmzRx55JHcd999Dd5/1113cc899/Dggw/yxhtv0L59e0aPHk15efkBF6s2pGJjMKXlf78Jjj9zHXzpMUhrH25dkiRJzazRU1zOOOMMzjjjjAbvi8Vi3H333fzoRz/i3HPPBeCxxx4jLy+Pp556iosucndH7YMNy+GvF8HaRUEz6Jj7YfD5YVclSZLUIpp0bbply5ZRVFTEqFGjas/l5ORw3HHHMWvWrAY/p6KigrKysjo3tWHLZ8HDJwfhPCsPLnvecC5JktqUJg3oRUVFAOTl5dU5n5eXV3vfriZNmkROTk7trWdPd4JsE6LVsOwVWPD34N9oNbz1F/jj2cFKLd2OhK+/BD2Ghl2pJElSiwp9FZeJEycyYcKE2uOysjJDeqJbNBWm3QBlhTvOpWVB5abg4wHnwpgHnG8uKaG8s6qESc+9z8Qv9GNIj45hlyMpjjXpCHp+fj4AxcXFdc4XFxfX3rer9PR0srOz69yUwBZNhSmX1g3nsFM4HwPn/8FwLinh/HPeamZ99Cn/nLc67FIkxbkmDeh9+/YlPz+fGTNm1J4rKyvjjTfeYMSIEU35pdQaRauDkXNiu79m1Zw93y9JrciqDVtYsKqUhatLeebtYGDimbcLWbi6lAWrSlm1YUvIFUqKR42e4rJp0yaWLl1ae7xs2TLmz59Pbm4uvXr14uqrr+a2227jsMMOo2/fvtx0000UFBQwZsyYpqxbrdHy1+qPnO+qbHVwXd+TWqYmSWpGJ975Ur1zn26u5Kx7X609/viOM1uyJEmtQKMD+ptvvsnnP//52uPt88fHjRvHH/7wB66//no2b97MN77xDUpKSjjxxBOZNm0aGRkZTVe1WqdNxXu/pjHXSVIciUZjLP1kE3M+Xs+cZeuZ8/GGPV4ficCEUw8nFosRiURaqEpJrUEkFovF1XyCsrIycnJyKC0tdT56Iikvhae/C+89tfdrxz3rCLqkuFdVHWXh6lLmfLye2cs2MHf5ejZsqapzTXJShIMPas+StZt2+ziHdc1izNHdOefIAnrmtmvusiWFaF9zrgFdzSsahXf+BtNvhs1r93JxBLIL4OoFkJTcIuVJ0r7aXLGNt1aUMPvj9bz58XreWlHC1qrqOtdkpCZxTK9ODOuTy7F9cjm6V0eWrdvMWfe+SiQCsRi1/55waGfmfLyBym3R2s8f3qcT5x7VnTMHd6NT+7SW/i9Kamb7mnNDX2ZRCWzN2/DcdbDyjeC486Ew8Ivw8i9qLtj5b8Oat3dPv8NwLikurN9cudN0lfUsLCyjOlp3TKtju1SG9c7l2L6dGN4nl0Hdc0hNrrv+QuesNLpkpdOtYwYXDu/J3+asZE1JOb/40pG0T09h2oIinpofrPAy5+MNzPl4A7c+8y6fPbwrY44uYFT/PDJS/b0otSWOoKvpbVkP/7kN5j4KsSiktofPXgfHj4eUtIbXQc/uHoTzAeeEV7ekNisWi7Fqw9YgkH+8ntnL1vPhJ5vrXde9YybD+9SMkPfN5dAuWSQl7X3+eMW2atKSk4hEIsRiMSqro6Sn1A3dRaXlTH17NU+9VciiNTt21c5KT2H0wHy+eHR3RhzSmeR9+HqS4pNTXNTyotXw1p/gxVth6/rg3KCxcOpPIad7/WuXvxY0hGblQe+RjpxLajHRaIwlazcxe6cR8jWl5fWuO6xrFsP7BtNVhvfNpXvHzBap74PijTz11mqenl/I6pKttee7dkjnnCMLGHN0dwYWZNtcKrUyBnS1rFVvwnPXQuFbwXGX/vCFn9vsKSkuVG6LsqCmoXPOsvW8uXwDpVvrNnSmJEUY1D2HY/vmMqx3MEqeG/I88Gg0xtwVG3jqrdX8a8EaSnZqQj2kS3vGHNWdMUd3t7lUaiUM6GoZmz6BGT+Gt/4cHKdnw+cmwrFfh+TUUEtrDm7VLYVvX34ON1VsY97yDbz58Xpmf7ye+StLKK+K1rkmMzWZY3p3ZHhNQ+dRvTrSLi1+W7Mqt0WZ+cEnPDV/NS8uKqZip+bSob07MeaoAs4cUhD6HxVSPAv7ddwmUTWv6m3w5v/BS7cFSygCHPllGPVj6JAXamnNaeetug3oUjga+jlct6kiCOPLNjDn4/UsWlO/oTO3fRrDencKRsj75DKwILteQ2c8S0tJ4tQBeZw6II+N5VVMW1jE0/ML+d+H65i7fANzl2/g1mcW8dnDu3Du0d05tX8emWlOHZR21lpexx1BV+Mtfy1YnaV4YXCcPwS+8AvodVy4dTWTVRu2sGFzFZEIjPu/2Xy6uZLO7dP44+XHEotBp/ap9Ojk28tSc2ro5zArPYURB3dm0ZpSVpfUnz/evWMmx/bNDUbI+3bikC5ZCTlnu7isnGfeLuSp+atZuHpHc2n7tGRGD8pnzFHdGXlIZ1Ja0R8jUlOKp9dxp7io6ZWtCdYzXzAlOM7oCKfcDEO/lrANnqVbqzjy1n/v9bqfnDuQ7h0zKai55WQm3vQeqaWUV1WzprSc1Ru2UliyldUlW/nNjCV7/bwj8jowvGa5w+F9cilooYbOeLJ07UaeeisI66s27Ggu7dIhnbOHFDDm6AIGd89JyD9UpIaUV1XT76Zpe73u4zvObIFqDOhqStVV8PoDMPNOqNwERGDoODj5ZmjfOezqmlRxWXltE9nsjzfwflEZ+/MT0iE9hYKOmXTvlElBxwy6d2xX829wrmuHDJdKU5sUi8Uo2VLF6prgXViyNQjipcG/q0vKWbepolGPmRSBn44ZxCXH9W6mqlufWCzGvBUbePKt1fzrnTV1djg9eHtz6VHd6dXZd/+UWMrKq5j78YbaFZreWVVKZXV0t9enJEX4xZeOZMzR3Xd7TZPWZ0BXk/jwJXj+Bli3ODjuPixYnaX7MeHW1QRisRjL1m2u3aZ7zsfrWbF+S73r+nRux6Fds3jxvfo7oV5xYh+iMWoDRmFJOes3V+71a6ckRcjPyaCgYyY9dhp5794pk+4dg/NN1awWdkOM4ltTf39UVUcpKi2vHfkO/i2v/biwZCtbKqv3+jiZqck1f+BmBn/YdswgGovxq+n1R9KfvepEBnXPOeDaE1Xltigv1zSXTt+lufSYXh0Zc3Swc2nnrPR6n+vvD8W7tWXltWF8dwNrB2Wlc0R+Fv9b+mm9z2/p3x82ierAlKyEf/8QFj0dHLc7CE69NWgETWqd8xi3VUd5b83G2m2653y8nnWb6obpSAT652fXzlsd3qcTXbMzWLi6lBffW1tvq+4vHt2j3g/2lsptFO4USHZ+m351yVaKSsvZFg02RVm1YSuzd1Nvp3apQUDJCUJKj53CSkHHTA7KStunt6lbS0OMwtHY74+N5VU1399bWF1SXu97vLisnOg+DPsclJVO944Ztd/jdcN4Jh3bpdb7/l64upRfTV9S7+dQe5aWksSoAXmMGpDHpoptvLAw2Ln0f0vXMW9FCfNWlPCTZxZx0mEHMebo7pw6IK92gMDfH4on+zqw1rtzu9rVmYb3zaVP53a8W1jGWfe+2mp+fxjQVde2CnjtHnj5l7BtK0SSYPjX4fMTIbNT2NU1SnlVNfNXltT8Vb2et1aUsKliW51r0lKSOKpHx9p5q8f07kR2Rv3547vbqrtzVv3lzNqlpXBo1ywO7ZrVYF3V0RhrNwbBZtWGrbVhp3CnsLOxYhsbtlSxYUtVnaavXWsPwnpGbWjfHm6SIhFSUyKkpyTzzNvBjq3PvF3I+UN72NiqOg1TO39/nHd0d9ZvqWRrVTXbqmN1RsFX1YTwsvJte3l0SEtOolsD35fbQ3i3nIz92rq+MT+HalhWegpjh/Zg7NAerC0r55l31vD0/NW8s6qUlxZ/wkuLPyEjNYnjD+7M54/o6u8PhWpbdZT3izYyu2YzsTkfb6g3BW53A2u7am2/P5zioh0++DdMuwHWfxQc9xoZTGfJHxRuXfuodEsVby5fX/tW14LVpVRV1/327pCewtA+nWpWdchlcPecfQ4K+7JVd1MpK6+qN/JeWFLO6g1BkC/eWH7Af/nPv/lUcjLrj1Iq8fW58V8H9Pk5mam14btHA30WB2Wlk9RMPRYt+XPYlnz4ySaefms1T80vbHBEcleLfjI6rteMV+u0TwNryUkc2TMnCON9cxm6m4G1hsTD7w/noGvfrf8Ipv0APng+OM7Kh9Nug8HnB3+axqmi0vI623QvLt5YL7R27ZC+Y5vuPrkckd8hIZozK7dFKS4rrx3V3DHXN7itXL+l3h8nDWmflrzL/PcdU2i6d8okr0O6S7MlgFgsxkfrNte+6P138VrWb67a7fWd2qVyaNesOt8LO0+vyko3mCWqWCzG3S8u4Z7/LNnrIEBu+zQKOmbUTlHa+fdHY6bhqe0q3VrF3OU7pqssaKCh80AG1uKRAV17V7kFXv01/O83UF0BSSlw/LfhszdAeoewq6sjFovx4Seba1dYmbN8PSvXb6133cEHtWfYTj/IvXLbtckXiFgsxv+WruMrj9Sf4X5o1yw2bK7k031oZk2KQH52Rr2Atv3F2LAWn7ZVR1m0pozZy9bz5scbeHN5A/0WQEO//J/6zkiO6tW6prOp6S1cXcpZ975a73zv3HZ8urmy3qhmQ7ZPw9s+FW/X6U75ORm++9HGNGZgbXjvTgzvm0u//OyEGFjbziZR7V4sBu8/G4yal64Izh38OTjjLuhyRIuVsafVAbZVR3m3sKxmzlkQMnYNlEkRGFCQXdsIMqxPLl061F+FoC2KRCJ0bJdW83Hdhpi7LzyKQd1zKK+qrrOyxvYl7rbPh19TupWq6hiFpeUUlpYDGxr8WjmZqXVW2tge5revULO/0x1cPWLflVdV89aKktqfl3nLN7B5l5VSdu23yEhN5qKHXq/3/eE7JtrZrt8f911yDIO651C6tWrH747tt53e0Vu7sYLKbVGWrdvMsnWbd/v4XTuk7/j90SmTgpwMunfaMV1qf6bh+buj5ezpud71nbs5Hzc8sNb3oPYMd2CtHgN6W7NuCTx/PXz4n+A4uwec/jPof06LT2fZeXWAw7p24K2VG5hT8zbXvBUb6i3Flp6SxFE9O9bOOzumV0c67OO8s7Zobw0xGanJHNIli0O6NNzMGo3G+GRTRb0X3l0bBku3VlG6tYr31uymmbWmYbDuSh075iwXdMxs8O1KV4/YvZItlbz58YbaQN5gv0VGCsNqRqCO7ZPL4B45dUYr15RubVUNU2pZe/v9kZOZSk5mKv27NTwCuLdpeIUlWymvirJ2YwVrN1Ywf2VJg4+zfRrerqv87Gkanr87Ws7Oz/WAbtm179zty8Da8D65DOvTia4d6jd0yikubUfFRnj55zDrfohWQXIanPA9OHECpLVcN/721SM2VVTxjT/NZWP5NlKSgjfbt+2yj0B2RgrD+uzYpntQ9xzfDm2k5m6I2b7kXmHJVlbtsqxkYclWivZ5yb00CjpmktsujZx2qXTtkM7js1eysWIbue1S+ePlxwKRNrt6xJrSrTtWMVi2gcXFG+tdk5edXvuit6/9FvHQMKX41ZzfH7FYjPWbKxtesrNm06p9mYaXnBQhPzuDzlmpdGqXRtcOGTy3YA2bK6vJbZ/GYyFs5Z7otr+OV1ZXc9mjcygr30ZqcoTkSITyXV7I02oG1o51YK2Wc9AViMVg4T/g3z+CjWuCc4eNhtMnQedDWqyMwpKtzPl4Pd97fP5er/3JuQODgJHXodlWglDLqKoORtF23shp5xG11Ru2srVq75vW7OziY3vWWzc7PyeD1ASZmhH0W2yqbZqa8/H6Olu2b3fwQe1r3006tk8uPXMzfVtYCWVfp+Htqzk/HOU0yAOw/Z27//fYm3u99obT+zG8T6d679zJgN52RKth+WuwqRiy8qD3SEiq+WEofheeux6W1zT6dOoDp98JR5zerCXFYjGWrt1UsyHQBmYvW8/qkvoBY1ctvd2uwrfztu+FJVt5vmYDlcb+VopEIK9DRr2dJ3eeD7+vy3C1tJ37LWYvW8+byzfU2402KQIDC3Jq1/i130KqOw3vqbdW8+fXl+/1HTvnO++77QNre3rnble+ju+dAb0tWDQ1WLe8rHDHuewCOPlmWPM2zH4IYtWQkgknfR9GXgWpTT/Xq2p7wKhpBHnz4/Vs2FJ3CbfkpAgDC7IZ1juX/Ox0fvb8+/Uex+26BbtfPeK2MYNIS0mqNx++sKS83rJcDemQkVJv/urOc1q7dEg/4JUC9qU5bWtlNW+t2FDbNPXWipLd9lts33jjmN6dXC1H2ovd/e44c3A+H36yefcrhtT84ZuIK4bsq13fudvdwNrBXdpzbJ9c8nMyuPvFJfXu93V871zFJdEtmgpTLqXeQmllhfDUt3Yc9z8HRt8OHXs12ZfeUrmNt1aU1Iz2rWfe8pJ60xTSU5I4uteOeWdH99oRMBauLgXqrw4g7WzX74+jenZs8Bd/NBpj3eaKmo2cGlhVonQrJVuq2Fi+jfeLNvJ+UcOjQKnJEfJzGl7Teft29Jlpe36rtqHmtA2bK3lz+Y4XvYWrS9m2yzBfdkZK7XSV4X1yGdQ927eFpf206++Ob3/u0GDlmS1VzF2xY83td1aVsHZjBf9asIZ/LQimgO685vbwPrkM6dG619zenZ0H1uZ8vPd37o7tG7xzd1BW8M7dwtWl3P3iEl/Hm5EBvTWKVgcj5w2uYlwjKQUufhwOO/WAv9yGzZW1b3PN/ngD7zYQMHIyU2vfNhzWJ9hIIC2l4TnBrW27XbWsxn5/JCVF6Nohg64dMjiqZ8cGr9lUsY01u6wgEYT5clbXNLNWVcdYuX5rsAzYsoZry22fVrum8/ZVaDJTk8hMS6Frh/TabdH/PncVRWXlLCosZUUDy4rlZ2fUzB0PRu0O72q/hXSg9rryTLtUTu6Xx8n98oBgjvvbK0tqX9vmLd/Axopt/HfxJ/x38SdA0OR4ZI/927Uynmyp3Mb8FSV7fedudwNru/J1vPk5xaU1WvYK/PGsvV837lnoe1KjH37Vhi01o30bePPj9SxZu6neNd1yMuo0qB3WNatRAcPVI7QnLf39sa06SvHGitpmtHpLw23YWm9d8cY4pEv72ukqw/vk0qOTDZ1ScziQ3x3bqqO8X7Rxx4pJHzewwVcE+udn106JObZPLl2z42+ZwH0dWNu+FOvwvQysNcTX8f3jHPREFa2Gl26HV36592vHPgKDz9/zw0VjLP1k005LuK2v2ZSmrkO7Zu14m6u3AUNtSywWo2zrNlbVrB6xesMWCkuD0fcFq0pZsX5Lg5+XFIFbzxnIV0f0admCJR2wWCzGx59uqbPRzvJP6/+s9+7crnbDvOF9c+nTueUbT1eXbN1R57LmGVhT0zCgJ5JYDIoWwDt/C5ZM3L5c4t40MIJeuS3KwsLSOvPOShpo6By0fSOBmr+sc9v7tpW0O7trTrNhSkosxWXltYNZsz/ewPtFZfXmXh+UlV5npZj+3Zq28XRfB9Z85y4+2SSaCDYshwVPBLdPdlr1JD0botugquFRO4gEq7n0HsnmipqGzpof4rdWbqC8qu6KF5mpyRzdq2PtL5OjenakvStGSI1mw5SU2PKyMzhrSAFnDSkAoHRrFfNWbKgd9Hp7ZSnrNlXw/MIinl9YBEBWegrH9O4U9Jz0yeXInh0bbDzd3SpQVdVRFqwu5c3tU0+Xr9/rwNqw3p3onOVSrK2ZKSzebFkP7z4ZhPIVs3acT06Hw0fDkAuDxs8PXqhZxQV2bhaNEfx1/PcuV/Kn+2fxbmEZ1bvMO+vYLpVhvYPpKsGKETkJs8mLFAYbpqS2KSczlc8f0ZXPH9EVCBpP31lVWrtq0/bG05c/+ISXP6hpPE1OYnCPHaujDO2dS05mau0qUFPmrKRs67Y9DqxlpCZxdM8d8+CP7uXAWqJxiks8qNoKi58PQvmS6RDd/pdxBPqcGITy/mdDZsfaT1m1YQvbFj5N/ms/JmNrUe35wlhnbq36Ki9Ej609171jZp2GlkO6OO9Mamo2TEnaVXU0xvtF25czDPY/+GRjRb3r+nRux5rSciq2NbyngwNricM56PEuWg3LXg5C+aKpULnT2sz5g2HwBTBoLOTs2I0rGo3xwdqNzFm2npuefheAJKIcm/Q+XSlhLR2ZHe1HlOCH9u4Lj2J431y6d8xs0f+aJEmqLxaLsfzTLbWj40/MXbXXz/n3NZ/hUAfWEoZz0ONRLBbs8LngCVjwd9i0Y+SbnF7BiitDLoCu/YGgoXPB8h3LHb65fAOlW+vOO4uSxOvRAXXOudWuJEnxJxKJ0Oeg9vQ5qD0XDOvJCYcexPefeLveVFTY8Vp+eF6HECpV2AzoLWHDx0Eof+cJWLd4x/mMjjDwi0Eo73k8m6qizFu+gTnzFzN72Xrmryyp93ZXu7RkjukVvMV1UFYaP3xqYb0v99T4E1w5QpKkODfm6O4c2jWrwVWgfC1v2wzozWXLenj3n0EoX/n6jvMpGXD46TDkAj7J/wxvrtzE7HfWM2fq/1hUWMauf0Tntk9jWO9OtUslDSjIrp13tnB1KeDKEZIktXa+lmtnBvSmVLkFPng+COVLpwdLIQIQIdb3M6w/5Iu8kjKCWasqmfPsej5a93K9h+jRKbN2s4PhfTpxSJes3a5b6soRkiS1br6WqyE2iR6oaDUsmwnvTIH3noHKHbt3be08iIWdR/PktuOZsSqJ4rL6ndtH5HVgeN8dGxp0y2lcQ6crR0iS1Lr5Wt522CS6P6LVsPw12FQMWXnQeyQkNfADEovBmvlBKF/4j+D6GmUZBcxM+xwPlw3jndX5sBogaOxMTY4wuHtO7XKHw3rnktMu9YBK3vkHOBKJ+AMtSVIr42u5dmVA327RVJh2A5QV7jiXXQCn3wkDzgmO1y+rafacAp8uqb1sY6QDU6uP559VI5lbfjjUbBbUPi25ZvewXIb1CXbozEzzh06SJEm7Z0CHIJxPuZSdd+QEoGxNcP6YS6la8y6pa96svas8lsr06FCeqj6Bl6NHUkUKnduncXrN/PFj++TSv1sHUtxIQJIkSY1gQI9Ws+2560kmRv1WzBgxIDLvj6QC1bEI/4sO4unqE3ghOozc3IMY3ieX22rmkPc9qP1uGzolSZKkfWFAX/4aKZvW7Pbu7XH7sepRTMu9lEMPPoTP9cnl+r655GVntEyNkiRJajMM6Ds1eO7J+WO+xKVDz23mYiRJktTWOUE6K2+fLmuX272ZC5EkSZKaMaDfd9999OnTh4yMDI477jhmz57dXF/qwPQeCdkFDc5AB4Lz2d2D6yRJkqRm1iwB/W9/+xsTJkzglltuYd68eRx55JGMHj2atWvXNseXOzBJycFSikB0l7tqj0+/o+H10CVJkqQm1iwB/Ve/+hVf//rXueyyyxgwYAAPPvgg7dq14//+7/+a48sduAHnELngMSIdCuqcjmR3J3LBYzvWQZckSZKaWZM3iVZWVjJ37lwmTpxYey4pKYlRo0Yxa9asetdXVFRQUVFRe1xWVtbUJe2bAecQ6XdmnZ1EI7vbSVSSJElqJk0e0NetW0d1dTV5eXWbL/Py8nj//ffrXT9p0iRuvfXWpi5j/yQlQ9+Twq5CkiRJbVjoq7hMnDiR0tLS2tvKlSvDLkmSJEkKTZOPoB900EEkJydTXFx3ffHi4mLy8/PrXZ+enk56enpTlyFJkiS1Sk0+gp6WlsbQoUOZMWNG7bloNMqMGTMYMWJEU385SZIkKaE0y06iEyZMYNy4cQwbNoxjjz2Wu+++m82bN3PZZZc1x5eTJEmSEkazBPQLL7yQTz75hJtvvpmioiKOOuoopk2bVq9xVJIkSVJdkVgsFgu7iJ2VlZWRk5NDaWkp2dnZYZcjSZIkNYl9zbmhr+IiSZIkaQcDuiRJkhRHDOiSJElSHDGgS5IkSXHEgC5JkiTFEQO6JEmSFEcM6JIkSVIcaZaNig7E9mXZy8rKQq5EkiRJajrb8+3etiGKu4C+ceNGAHr27BlyJZIkSVLT27hxIzk5Obu9P+52Eo1GoxQWFtKhQwcikUiLf/2ysjJ69uzJypUr3cm0mflctwyf55bjc90yfJ5bjs91y/G5bhlhP8+xWIyNGzdSUFBAUtLuZ5rH3Qh6UlISPXr0CLsMsrOz/QFpIT7XLcPnueX4XLcMn+eW43PdcnyuW0aYz/OeRs63s0lUkiRJiiMGdEmSJCmOGNB3kZ6ezi233EJ6enrYpSQ8n+uW4fPccnyuW4bPc8vxuW45Ptcto7U8z3HXJCpJkiS1ZY6gS5IkSXHEgC5JkiTFEQO6JEmSFEcM6JIkSVIcMaBLkiRJccSAvov77ruPPn36kJGRwXHHHcfs2bPDLimhTJo0ieHDh9OhQwe6du3KmDFjWLx4cdhltQl33HEHkUiEq6++OuxSEs7q1av5yle+QufOncnMzGTw4MG8+eabYZeVcKqrq7npppvo27cvmZmZHHLIIfz0pz/FxcgO3Msvv8zZZ59NQUEBkUiEp556qs79sViMm2++mW7dupGZmcmoUaNYsmRJOMW2Ynt6nquqqrjhhhsYPHgw7du3p6CggEsvvZTCwsLwCm7F9vY9vbNvfetbRCIR7r777harb28M6Dv529/+xoQJE7jllluYN28eRx55JKNHj2bt2rVhl5YwZs6cyfjx43n99deZPn06VVVVnHbaaWzevDns0hLanDlz+N3vfseQIUPCLiXhbNiwgRNOOIHU1FSef/55Fi1axC9/+Us6deoUdmkJ58477+SBBx7gt7/9Le+99x533nknd911F/fee2/YpbV6mzdv5sgjj+S+++5r8P677rqLe+65hwcffJA33niD9u3bM3r0aMrLy1u40tZtT8/zli1bmDdvHjfddBPz5s3jn//8J4sXL+acc84JodLWb2/f09s9+eSTvP766xQUFLRQZfsoplrHHntsbPz48bXH1dXVsYKCgtikSZNCrCqxrV27NgbEZs6cGXYpCWvjxo2xww47LDZ9+vTYZz/72dj3vve9sEtKKDfccEPsxBNPDLuMNuHMM8+MXX755XXOnXfeebFLLrkkpIoSExB78skna4+j0WgsPz8/9vOf/7z2XElJSSw9PT3217/+NYQKE8Ouz3NDZs+eHQNiy5cvb5miEtTunutVq1bFunfvHlu4cGGsd+/esV//+tctXtvuOIJeo7Kykrlz5zJq1Kjac0lJSYwaNYpZs2aFWFliKy0tBSA3NzfkShLX+PHjOfPMM+t8b6vpTJ06lWHDhvGlL32Jrl27cvTRR/Pwww+HXVZCGjlyJDNmzOCDDz4A4O233+bVV1/ljDPOCLmyxLZs2TKKiorq/A7JycnhuOOO8/WxmZWWlhKJROjYsWPYpSScaDTKV7/6Va677joGDhwYdjn1pIRdQLxYt24d1dXV5OXl1Tmfl5fH+++/H1JViS0ajXL11VdzwgknMGjQoLDLSUiPP/448+bNY86cOWGXkrA++ugjHnjgASZMmMAPfvAD5syZw3e/+13S0tIYN25c2OUllBtvvJGysjL69etHcnIy1dXV3H777VxyySVhl5bQioqKABp8fdx+n5peeXk5N9xwAxdffDHZ2dlhl5Nw7rzzTlJSUvjud78bdikNMqArNOPHj2fhwoW8+uqrYZeSkFauXMn3vvc9pk+fTkZGRtjlJKxoNMqwYcP42c9+BsDRRx/NwoULefDBBw3oTWzKlCn85S9/YfLkyQwcOJD58+dz9dVXU1BQ4HOthFJVVcUFF1xALBbjgQceCLuchDN37lx+85vfMG/ePCKRSNjlNMgpLjUOOuggkpOTKS4urnO+uLiY/Pz8kKpKXFdeeSXPPvssL730Ej169Ai7nIQ0d+5c1q5dyzHHHENKSgopKSnMnDmTe+65h5SUFKqrq8MuMSF069aNAQMG1DnXv39/VqxYEVJFieu6667jxhtv5KKLLmLw4MF89atf5ZprrmHSpElhl5bQtr8G+vrYMraH8+XLlzN9+nRHz5vBK6+8wtq1a+nVq1ft6+Py5cv5/ve/T58+fcIuDzCg10pLS2Po0KHMmDGj9lw0GmXGjBmMGDEixMoSSywW48orr+TJJ5/kP//5D3379g27pIR1yimnsGDBAubPn197GzZsGJdccgnz588nOTk57BITwgknnFBvqdAPPviA3r17h1RR4tqyZQtJSXVftpKTk4lGoyFV1Db07duX/Pz8Oq+PZWVlvPHGG74+NrHt4XzJkiW8+OKLdO7cOeySEtJXv/pV3nnnnTqvjwUFBVx33XW88MILYZcHOMWljgkTJjBu3DiGDRvGsccey913383mzZu57LLLwi4tYYwfP57Jkyfz9NNP06FDh9r5izk5OWRmZoZcXWLp0KFDvbn97du3p3Pnzs75b0LXXHMNI0eO5Gc/+xkXXHABs2fP5qGHHuKhhx4Ku7SEc/bZZ3P77bfTq1cvBg4cyFtvvcWvfvUrLr/88rBLa/U2bdrE0qVLa4+XLVvG/Pnzyc3NpVevXlx99dXcdtttHHbYYfTt25ebbrqJgoICxowZE17RrdCenudu3bpx/vnnM2/ePJ599lmqq6trXyNzc3NJS0sLq+xWaW/f07v+8ZOamkp+fj5HHHFES5fasLCXkYk39957b6xXr16xtLS02LHHHht7/fXXwy4poQAN3h599NGwS2sTXGaxeTzzzDOxQYMGxdLT02P9+vWLPfTQQ2GXlJDKyspi3/ve92K9evWKZWRkxA4++ODYD3/4w1hFRUXYpbV6L730UoO/m8eNGxeLxYKlFm+66aZYXl5eLD09PXbKKafEFi9eHG7RrdCenudly5bt9jXypZdeCrv0Vmdv39O7irdlFiOxmFuwSZIkSfHCOeiSJElSHDGgS5IkSXHEgC5JkiTFEQO6JEmSFEcM6JIkSVIcMaBLkiRJccSALkmSJMURA7okSZIURwzokiRJUhwxoEuSJElxxIAuSZIkxZH/D+qWn2r2lgIfAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9,6))\n",
    "y = np.random.randint(0,10,15)\n",
    "plt.plot(y,marker = '*') # 只给了一个参数，Y轴，X轴默认：从0~N\n",
    "plt.plot(y.cumsum(),marker = 'o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "11f5453d-eff0-4ba1-bb0a-3ad5a4ab32f8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T13:45:08.315618Z",
     "iopub.status.busy": "2024-11-29T13:45:08.315618Z",
     "iopub.status.idle": "2024-11-29T13:45:08.473727Z",
     "shell.execute_reply": "2024-11-29T13:45:08.473727Z",
     "shell.execute_reply.started": "2024-11-29T13:45:08.315618Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2a62c9f5af0>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 多图布局\n",
    "fig,axes = plt.subplots(2,1)\n",
    "fig.set_figwidth(9)\n",
    "fig.set_figheight(6)\n",
    "axes[0].plot(y,marker = '*')\n",
    "axes[1].plot(y.cumsum(),marker = 'o')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ceeed4d9-317a-4f0b-9f7c-4aacecf071ac",
   "metadata": {},
   "source": [
    "# 条形图\n",
    "## 纵向条形图\n",
    "条形图的绘制方式跟折线图非常的类似，只不过是换成了plt.bar方法。plt.bar方法有以下常用参数：\n",
    "- x：一个数组或者列表，代表需要绘制的条形图的x轴的坐标点。\n",
    "- height：一个数组或者列表，代表需要绘制的条形图y轴的坐标点。\n",
    "- width：每一个条形图的宽度，默认是0.8的宽度。\n",
    "- bottom：y轴的基线，默认是0，也就是距离底部为0.\n",
    "- align：对齐方式，默认是center，也就是跟指定的x坐标居中对齐，还有为edge，靠边对齐，具体靠右边还是靠左边，看width的正负。\n",
    "- color：条形图的颜色。\n",
    "返回值为BarContainer，是一个存储了条形图的容器，而条形图实际上的类型是matplotlib.patches.Rectangle对象。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "24d2db1a-6875-4bc1-9651-19fd564d7bae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T13:50:29.294281Z",
     "iopub.status.busy": "2024-11-29T13:50:29.293166Z",
     "iopub.status.idle": "2024-11-29T13:50:29.460798Z",
     "shell.execute_reply": "2024-11-29T13:50:29.460294Z",
     "shell.execute_reply.started": "2024-11-29T13:50:29.294281Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.YTick at 0x2a62ce023d0>,\n",
       "  <matplotlib.axis.YTick at 0x2a62cb0da30>,\n",
       "  <matplotlib.axis.YTick at 0x2a62cded5b0>,\n",
       "  <matplotlib.axis.YTick at 0x2a62d541490>,\n",
       "  <matplotlib.axis.YTick at 0x2a62d541f40>,\n",
       "  <matplotlib.axis.YTick at 0x2a62d538490>,\n",
       "  <matplotlib.axis.YTick at 0x2a62d5459a0>,\n",
       "  <matplotlib.axis.YTick at 0x2a62d54d490>,\n",
       "  <matplotlib.axis.YTick at 0x2a62d54df40>],\n",
       " [Text(0, 0, '0亿'),\n",
       "  Text(0, 5, '5亿'),\n",
       "  Text(0, 10, '10亿'),\n",
       "  Text(0, 15, '15亿'),\n",
       "  Text(0, 20, '20亿'),\n",
       "  Text(0, 25, '25亿'),\n",
       "  Text(0, 30, '30亿'),\n",
       "  Text(0, 35, '35亿'),\n",
       "  Text(0, 40, '40亿')])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "movies = {\n",
    "    \"流浪地球\":40.78,\n",
    "    \"飞驰人生\":15.77,\n",
    "    \"疯狂的外星人\":20.83,\n",
    "    \"新喜剧之王\":6.10,\n",
    "    \"廉政风云\":1.10,\n",
    "    \"神探蒲松龄\":1.49,\n",
    "    \"小猪佩奇过大年\":1.22,\n",
    "    \"熊出没·原始时代\":6.71\n",
    "}\n",
    "x = list(movies.keys())\n",
    "y = list(movies.values())\n",
    "plt.figure(figsize=(15,5))\n",
    "# plt.bar(x,y,width=-0.3,align=\"edge\",color='r',edgecolor='k')  # 可以使用列表，也可以使用dataframe\n",
    "movie_df = pd.DataFrame(data={\"names\":list(movies.keys()),\"tickets\":list(movies.values())})\n",
    "plt.bar(\"names\",\"tickets\",data=movie_df)\n",
    "plt.xticks(size=12)  \n",
    "plt.yticks(range(0,45,5),[\"%d亿\"%x for x in range(0,45,5)],size=12)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85fb7f4f-6d92-4665-b99b-5af2cd3475c6",
   "metadata": {},
   "source": [
    "## 横向条形图\n",
    "横向条形图需要使用plt.barh这个方法跟bar非常的类似，只不过把方向进行旋转。参数跟bar类似，但也有区别。如下：\n",
    "- y：数组或列表，代表需要绘制的条形图在y轴上的坐标点。\n",
    "- width：数组或列表，代表需要绘制的条形图在x轴上的值（也就是长度）。\n",
    "- height：条形图的高度，默认是0.8。\n",
    "- left：条形图的基线，也就是距离y轴的距离。\n",
    "- 其他参数跟bar一样。\n",
    "- 返回值也是BarContainer容器对象。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "92c4670f-330c-4280-bb13-c49c7fd5f9a0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T13:52:08.173559Z",
     "iopub.status.busy": "2024-11-29T13:52:08.172267Z",
     "iopub.status.idle": "2024-11-29T13:52:08.328978Z",
     "shell.execute_reply": "2024-11-29T13:52:08.327976Z",
     "shell.execute_reply.started": "2024-11-29T13:52:08.173559Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([0, 1, 2, 3, 4, 5, 6, 7],\n",
       " [Text(0, 0, '流浪地球'),\n",
       "  Text(0, 1, '飞驰人生'),\n",
       "  Text(0, 2, '疯狂的外星人'),\n",
       "  Text(0, 3, '新喜剧之王'),\n",
       "  Text(0, 4, '廉政风云'),\n",
       "  Text(0, 5, '神探蒲松龄'),\n",
       "  Text(0, 6, '小猪佩奇过大年'),\n",
       "  Text(0, 7, '熊出没·原始时代')])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.barh(list(movies.keys()),list(movies.values()))\n",
    "plt.yticks(size=12)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "72c0bd24-c86c-4d0e-87e5-9df17cfb0fe0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T13:52:15.819834Z",
     "iopub.status.busy": "2024-11-29T13:52:15.819834Z",
     "iopub.status.idle": "2024-11-29T13:52:15.834940Z",
     "shell.execute_reply": "2024-11-29T13:52:15.833768Z",
     "shell.execute_reply.started": "2024-11-29T13:52:15.819834Z"
    }
   },
   "source": [
    "## 分组条形图\n",
    "matplotlib并没有提供专门的分组条形图的API来实现。而是需要设置这个坐标来实现。需要找到规律，算好每一个分组下，不同的条形数据显示的位置"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "8ec4eca5-d995-4744-af0f-be6b2bd7f9a2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T14:04:59.470580Z",
     "iopub.status.busy": "2024-11-29T14:04:59.470580Z",
     "iopub.status.idle": "2024-11-29T14:04:59.643200Z",
     "shell.execute_reply": "2024-11-29T14:04:59.642108Z",
     "shell.execute_reply.started": "2024-11-29T14:04:59.470580Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2a62c95cd30>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x900 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y1 = np.random.randint(20,35,6) # 男\n",
    "y2 = np.random.randint(20,35,6) # 女\n",
    "x = np.arange(6)\n",
    "labels = np.array(['G1','G2','G3','G4','G5','G6'])\n",
    "\n",
    "width = 0.4\n",
    "plt.figure(figsize=(12,9))\n",
    "bars = plt.bar(x - width/2,y1,width = width)\n",
    "for i,bar in enumerate(bars):\n",
    "    h = bar.get_height()\n",
    "    w = bar.get_width()\n",
    "    plt.text(x = bar.get_x() + w/2 ,\n",
    "             y = h + 0.5,s = y1[i],ha = 'center')\n",
    "\n",
    "bars = plt.bar(x + width/2,y2,width = width)\n",
    "\n",
    "for i,bar in enumerate(bars):\n",
    "    h = bar.get_height()\n",
    "    w = bar.get_width()\n",
    "    plt.text(x = bar.get_x() + w/2 ,\n",
    "             y = h + 0.5,s = y2[i],ha = 'center')\n",
    "    \n",
    "plt.legend(['Men','Women'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0b3eab76-9f21-45f5-804f-bbba90da51fc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T14:05:59.972579Z",
     "iopub.status.busy": "2024-11-29T14:05:59.972579Z",
     "iopub.status.idle": "2024-11-29T14:06:00.289404Z",
     "shell.execute_reply": "2024-11-29T14:06:00.288211Z",
     "shell.execute_reply.started": "2024-11-29T14:05:59.972579Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>流浪地球</th>\n",
       "      <th>飞驰人生</th>\n",
       "      <th>疯狂的外星人</th>\n",
       "      <th>新喜剧之王</th>\n",
       "      <th>廉政风云</th>\n",
       "      <th>神探蒲松龄</th>\n",
       "      <th>小猪佩奇过大年</th>\n",
       "      <th>熊出没·原始时代</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.01</td>\n",
       "      <td>3.19</td>\n",
       "      <td>4.07</td>\n",
       "      <td>2.72</td>\n",
       "      <td>0.56</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.58</td>\n",
       "      <td>1.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.59</td>\n",
       "      <td>5.08</td>\n",
       "      <td>6.92</td>\n",
       "      <td>3.79</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.95</td>\n",
       "      <td>0.81</td>\n",
       "      <td>1.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7.99</td>\n",
       "      <td>6.73</td>\n",
       "      <td>9.30</td>\n",
       "      <td>4.45</td>\n",
       "      <td>0.83</td>\n",
       "      <td>1.10</td>\n",
       "      <td>0.94</td>\n",
       "      <td>2.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.83</td>\n",
       "      <td>8.10</td>\n",
       "      <td>11.29</td>\n",
       "      <td>4.83</td>\n",
       "      <td>0.88</td>\n",
       "      <td>1.17</td>\n",
       "      <td>1.01</td>\n",
       "      <td>3.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>16.00</td>\n",
       "      <td>9.35</td>\n",
       "      <td>13.03</td>\n",
       "      <td>5.11</td>\n",
       "      <td>0.92</td>\n",
       "      <td>1.23</td>\n",
       "      <td>1.07</td>\n",
       "      <td>4.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    流浪地球  飞驰人生  疯狂的外星人  新喜剧之王  廉政风云  神探蒲松龄  小猪佩奇过大年  熊出没·原始时代\n",
       "0   2.01  3.19    4.07   2.72  0.56   0.66     0.58      1.13\n",
       "1   4.59  5.08    6.92   3.79  0.74   0.95     0.81      1.96\n",
       "2   7.99  6.73    9.30   4.45  0.83   1.10     0.94      2.73\n",
       "3  11.83  8.10   11.29   4.83  0.88   1.17     1.01      3.42\n",
       "4  16.00  9.35   13.03   5.11  0.92   1.23     1.07      4.05"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 2000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "movies = {\n",
    "    \"流浪地球\":[2.01,4.59,7.99,11.83,16],\n",
    "    \"飞驰人生\":[3.19,5.08,6.73,8.10,9.35],\n",
    "    \"疯狂的外星人\":[4.07,6.92,9.30,11.29,13.03],\n",
    "    \"新喜剧之王\":[2.72,3.79,4.45,4.83,5.11],\n",
    "    \"廉政风云\":[0.56,0.74,0.83,0.88,0.92],\n",
    "    \"神探蒲松龄\":[0.66,0.95,1.10,1.17,1.23],\n",
    "    \"小猪佩奇过大年\":[0.58,0.81,0.94,1.01,1.07],\n",
    "    \"熊出没·原始时代\":[1.13,1.96,2.73,3.42,4.05]\n",
    "}\n",
    "movie_df = pd.DataFrame(movies)\n",
    "display(movie_df)\n",
    "\n",
    "plt.figure(figsize=(20,5))\n",
    "# for index in movie_df.index:\n",
    "#     series = movie_df.iloc[index]\n",
    "#     plt.bar(series.index,series.values)\n",
    "xticks = np.arange(0,len(movies)*1.5,1.5)\n",
    "bar_width = 0.2\n",
    "# -2 -1 0 1 2\n",
    "# plt.bar(xticks-2*bar_width,movie_df.iloc[0],width=bar_width) # 绘制所有电影第一天的数据\n",
    "# plt.bar(xticks-bar_width,movie_df.iloc[1],width=bar_width) # 绘制所有电影第二天的数据\n",
    "# plt.bar(xticks,movie_df.iloc[2],width=bar_width) # 绘制所有电影第三天的数据\n",
    "# plt.bar(xticks+bar_width,movie_df.iloc[3],width=bar_width) # 绘制所有电影第四天的数据\n",
    "# plt.bar(xticks+2*bar_width,movie_df.iloc[4],width=bar_width) # 绘制所有电影第五天的数据\n",
    "for index in movie_df.index:\n",
    "    day_tickets = movie_df.iloc[index]\n",
    "    xs = xticks-(bar_width*(2-index))\n",
    "    plt.bar(xs,day_tickets,width=bar_width,label=\"第%d天数据\"%(index+1)) # label参数为了绘制 分组条形图的图例\n",
    "    for ticket,x in zip(day_tickets,xs):\n",
    "        plt.annotate(ticket,xy=(x,ticket),xytext=(x-0.1,ticket+0.1),size=8)\n",
    "plt.xticks(xticks,movie_df.columns,size=12)\n",
    "plt.ylabel(\"单位：亿\")\n",
    "plt.title(\"春节前5天电影票房记录\")\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "317ba076-cfb7-4291-91a9-c6dfdcc916d0",
   "metadata": {},
   "source": [
    "## 堆叠条形图\n",
    "matplotlib并没有提供专门的堆叠条形图的API来实现，我们在绘制往上堆叠的数据的时候，可以使用bottom参数，来往上偏移指定的距离。这样就可以实现堆叠的效果了。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "ecdb0242-f332-493e-8846-01c2c267e6d4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T14:08:35.088014Z",
     "iopub.status.busy": "2024-11-29T14:08:35.086983Z",
     "iopub.status.idle": "2024-11-29T14:08:35.214427Z",
     "shell.execute_reply": "2024-11-29T14:08:35.214427Z",
     "shell.execute_reply.started": "2024-11-29T14:08:35.088014Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2a62f0667c0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "menMeans = (20, 35, 30, 35, 27)\n",
    "womenMeans = (25, 32, 34, 20, 25)\n",
    "groupNames = ('G1','G2','G3','G4','G5')\n",
    "plt.bar(groupNames,menMeans,label=\"男性得分\")\n",
    "plt.bar(groupNames,womenMeans,bottom=menMeans,label='女性得分')\n",
    "plt.legend()\n",
    "# 在绘制女性得分的条形图的时候，因为要堆叠在男性得分的条形图上，所以使用到了一个bottom参数，就是距离x轴的距离。通过对贴条形图，我们就可以清楚的知道，哪一个队伍的综合排名是最高的，并且在每个队伍中男女的得分情况。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "f264b3c1-71bc-4df8-945a-0fba58a1a4a7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T14:09:04.749407Z",
     "iopub.status.busy": "2024-11-29T14:09:04.749407Z",
     "iopub.status.idle": "2024-11-29T14:09:04.906988Z",
     "shell.execute_reply": "2024-11-29T14:09:04.906988Z",
     "shell.execute_reply.started": "2024-11-29T14:09:04.749407Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2a62e8ecc10>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y1 = np.random.randint(20,35,6) # 男\n",
    "y2 = np.random.randint(20,35,6) # 女\n",
    "\n",
    "plt.figure(figsize=(9,6))\n",
    "x = np.array(['G1','G2','G3','G4','G5','G6'])\n",
    "\n",
    "# 误差条 yerr  \n",
    "plt.bar(x,y1,color = 'orange',width = 0.5,yerr = 4,ecolor = 'red',capsize = 5)\n",
    "plt.bar(x,y2,bottom = y1,width = 0.5,yerr = 2,ecolor = 'red',capsize = 5) # y2画到y1上面\n",
    "\n",
    "plt.legend(['Men','Women'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2225d169-4547-4caa-9d98-6add4f827e21",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T14:09:07.373302Z",
     "iopub.status.busy": "2024-11-29T14:09:07.372296Z",
     "iopub.status.idle": "2024-11-29T14:09:07.384143Z",
     "shell.execute_reply": "2024-11-29T14:09:07.384143Z",
     "shell.execute_reply.started": "2024-11-29T14:09:07.373302Z"
    }
   },
   "source": [
    "# 散点图\n",
    "散点图也叫 X-Y 图，它将所有的数据以点的形式展现在直角坐标系上，以显示变量之间的相互影响程度，点的位置由变量的数值决定。\n",
    "\n",
    "通过观察散点图上数据点的分布情况，我们可以推断出变量间的相关性。如果变量之间不存在相互关系，那么在散点图上就会表现为随机分布的离散的点，如果存在某种相关性，那么大部分的数据点就会相对密集并以某种趋势呈现。数据的相关关系主要分为：正相关（两个变量值同时增长）、负相关（一个变量值增加另一个变量值下降）、不相关、线性相关、指数相关等，表现在散点图上的大致分布如下图所示。那些离点集群较远的点我们称为离群点或者异常点。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4dcf99f-5a79-48e6-8398-e20df36968af",
   "metadata": {},
   "source": [
    "## 绘制散点图\n",
    "散点图的绘制，使用的是plt.scatter方法，这个方法有以下参数\n",
    "- x,y：分别是x轴和y轴的数据集。两者的数据长度必须一致。\n",
    "- s：点的尺寸。如果是一个具体的数字，那么散点图的所有点都是一样大小，如果是一个序列，那么这个序列的长度应该和x轴数据量一致，序列中的每个元素代表每个点的尺寸。\n",
    "- c：点的颜色。可以为具体的颜色，也可以为一个序列或者是一个cmap对象。\n",
    "- marker：标记点，默认是圆点，也可以换成其他的。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "811e0c90-0d2f-4b4d-ae53-58e1b3d18c70",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T14:53:29.102870Z",
     "iopub.status.busy": "2024-11-29T14:53:29.101842Z",
     "iopub.status.idle": "2024-11-29T14:53:29.127549Z",
     "shell.execute_reply": "2024-11-29T14:53:29.127549Z",
     "shell.execute_reply.started": "2024-11-29T14:53:29.102870Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>total_bill</th>\n",
       "      <th>tip</th>\n",
       "      <th>sex</th>\n",
       "      <th>smoker</th>\n",
       "      <th>day</th>\n",
       "      <th>time</th>\n",
       "      <th>size</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>16.99</td>\n",
       "      <td>1.01</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>10.34</td>\n",
       "      <td>1.66</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>21.01</td>\n",
       "      <td>3.50</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>23.68</td>\n",
       "      <td>3.31</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>24.59</td>\n",
       "      <td>3.61</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Sun</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>29.03</td>\n",
       "      <td>5.92</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>27.18</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>22.67</td>\n",
       "      <td>2.00</td>\n",
       "      <td>Male</td>\n",
       "      <td>Yes</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>17.82</td>\n",
       "      <td>1.75</td>\n",
       "      <td>Male</td>\n",
       "      <td>No</td>\n",
       "      <td>Sat</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>18.78</td>\n",
       "      <td>3.00</td>\n",
       "      <td>Female</td>\n",
       "      <td>No</td>\n",
       "      <td>Thur</td>\n",
       "      <td>Dinner</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     total_bill   tip     sex smoker   day    time  size\n",
       "0         16.99  1.01  Female     No   Sun  Dinner     2\n",
       "1         10.34  1.66    Male     No   Sun  Dinner     3\n",
       "2         21.01  3.50    Male     No   Sun  Dinner     3\n",
       "3         23.68  3.31    Male     No   Sun  Dinner     2\n",
       "4         24.59  3.61  Female     No   Sun  Dinner     4\n",
       "..          ...   ...     ...    ...   ...     ...   ...\n",
       "239       29.03  5.92    Male     No   Sat  Dinner     3\n",
       "240       27.18  2.00  Female    Yes   Sat  Dinner     2\n",
       "241       22.67  2.00    Male    Yes   Sat  Dinner     2\n",
       "242       17.82  1.75    Male     No   Sat  Dinner     2\n",
       "243       18.78  3.00  Female     No  Thur  Dinner     2\n",
       "\n",
       "[244 rows x 7 columns]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# # github中加载远程的数据集\n",
    "tips = sns.load_dataset(\"tips\")\n",
    "tips"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4f90fabb-c670-43dc-9388-5cb6ac7ca161",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T15:01:19.327853Z",
     "iopub.status.busy": "2024-11-29T15:01:19.327853Z",
     "iopub.status.idle": "2024-11-29T15:01:19.415019Z",
     "shell.execute_reply": "2024-11-29T15:01:19.415019Z",
     "shell.execute_reply.started": "2024-11-29T15:01:19.327853Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1500x500 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,5))\n",
    "male_tips = tips[tips['sex'] == 'Male']\n",
    "female_tips = tips[tips['sex'] == 'Female']\n",
    "male_mean_total = male_tips['total_bill'].mean()\n",
    "female_mean_total = female_tips['total_bill'].mean()\n",
    "male_mean_tip = male_tips['tip'].mean()\n",
    "female_mean_tip = female_tips['tip'].mean()\n",
    "\n",
    "plt.figure(figsize=(10,4))\n",
    "plt.scatter(male_tips['total_bill'],male_tips['tip'],s=male_tips['size'],marker='^',color='g',label='男性',alpha=0.5)\n",
    "plt.scatter(female_tips['total_bill'],female_tips['tip'],color='r',alpha=0.5,s=female_tips['size'],label='女性')\n",
    "plt.axvline(male_mean_total,color=\"g\",linewidth=1) # 绘制平均线\n",
    "plt.axhline(male_mean_tip,color=\"g\",linewidth=1)\n",
    "plt.axvline(female_mean_total,color=\"r\",linewidth=1)\n",
    "plt.axhline(female_mean_tip,color=\"r\",linewidth=1)\n",
    "plt.xticks(np.arange(0,50,10))\n",
    "plt.yticks(np.arange(0,10,10))\n",
    "plt.xlabel(\"账单金额（元）\")\n",
    "plt.ylabel(\"小费（元）\")\n",
    "plt.title(\"账单金额与小费散点图\")\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd14d334-901a-43a1-b97f-43d89336e57b",
   "metadata": {},
   "source": [
    "## 绘制回归曲线\n",
    "有一组数据后，我们可以对这组数据进行回归分析，回归分析可以帮助我们了解这组数据的大体走向。回归分析按照涉及的变量的多少，分为一元回归和多元回归分析；按照自变量的多少，可分为简单回归分析和多重回归分析；按照自变量和因变量之间的关系类型，可分为线性回归分析和非线性回归分析。如果在回归分析中，只包括一个自变量和一个因变量，且二者的关系可用一条直线近似表示，这种回归分析称为一元线性回归分析。如果回归分析中包括两个或两个以上的自变量，且自变量之间存在线性相关，则称为多重线性回归分析。\n",
    "|自变量数量|\t是否线性|\t回归类型|\n",
    "|---|---|---|\n",
    "|1个\t|是\t|一元线性回归|\n",
    "|多个\t|是\t|多元线性回归|\n",
    "|1个\t|否\t|一元非线性回归|\n",
    "|多个\t|否\t|多元非线性回归|\n",
    "\n",
    "通过以上散点图的分析，我们总体上可以看出来是满足线性回归的，因此可以在图上绘制一个线性回归的线条。想要绘制线性回归的线条，需要先按照之前的数据计算出线性方程，假如x是自变量，y是因变量，那么线性回归的方程可以用以下几个来表示：\n",
    "\n",
    "**y = 截距+斜率*x+误差**  \n",
    "只要把这个方程计算出来了，那么后续我们就可以根据x的值，大概的估计出y的取值范围，也就是预测。如果我们针对以上账单的金额和小费的关系，只要有金额，那么就可以大概的估计小费的值。回归方程的绘制我们需要借助scikit-learn库，这个库是专门做机器学习用的，我们需要使用里面的线性回归类sklearn.liear_regression.LinearRegression。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "f3dfb789-6921-455b-b92f-304601292148",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-11-29T15:12:39.743766Z",
     "iopub.status.busy": "2024-11-29T15:12:39.742760Z",
     "iopub.status.idle": "2024-11-29T15:12:41.277860Z",
     "shell.execute_reply": "2024-11-29T15:12:41.276857Z",
     "shell.execute_reply.started": "2024-11-29T15:12:39.743766Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.10786068]\n",
      "0.852147693932261\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "plt.figure(figsize=(8,4))\n",
    "male_tips = tips[tips['sex'] == 'Male']\n",
    "male_total = male_tips['total_bill']\n",
    "male_tip = male_tips['tip']\n",
    "plt.scatter(male_tips['total_bill'],male_tips['tip'],s=male_tips['size'],marker='^',color='g',label='男性',alpha=0.5)\n",
    "\n",
    "# 生成线性回归对象\n",
    "model = LinearRegression()\n",
    "# 喂训练数据进去，注意需要把因变量转换成1列多行的数据\n",
    "model.fit(male_total.values[:,np.newaxis],male_tip)\n",
    "'''\n",
    "代码一：male_total.values.reshape(male_total.shape[0],1)  \n",
    "解读代码：将数组数据转为二维数组，且为1列多行\n",
    "male_total：是数组\n",
    "代码二：male_total.values[:,np.newaxis]\n",
    "直接返回一个1列多行的二维数组\n",
    "'''\n",
    "# 打印斜率\n",
    "print(model.coef_)\n",
    "# 打印截距\n",
    "print(model.intercept_)\n",
    "predict_male_tip = model.predict(male_total.values[:,np.newaxis])\n",
    "plt.plot(male_total,predict_male_tip)\n",
    "plt.legend()\n",
    "plt.xlabel(\"账单（元）\")\n",
    "plt.ylabel(\"小费（元）\")\n",
    "plt.title(\"账单金额与小费散点图\")\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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